Wireless (e.g. mobile) data traffic amounts are growing rapidly and one difficulty encountered when attempting to deliver high data rates is the natural variability (e.g. fading) of the radio propagation channels.
Power control and adaptive modulation and coding are classical methods that adapt the signal quality and data rates to current radio channel conditions, and may be applied in one or both of the time dimension and the frequency dimension. The adaptation needs to be determined over the same time/frequency scale as the channel variation manifests itself, which may typically correspond to a few milliseconds and a few hundred kHz, and may hence require cumbersome channel estimation and feedback mechanisms.
In various situations, radio channel conditions may be stable or substantially stable over time and/or frequency. Such conditions may be referred to as “non-fading” channel conditions or a hardened channel environment, and they may appear due to the physical properties of a radio channel (as may be the case, for example, for a mini-link channel) or as a result of signal processing (as may be the case, for example, for communication systems applying massive MIMO (multiple-input, multiple-output)). For example, channel gain variation in a 256 antenna system may be expected to be in the order of 1 dB, while a traditional system (i.e. one with a low amount of antennas) under the same assumptions typically experiences more than 20 dB channel gain variation. Even smaller channel gain variation may be achieved by limiting the time and/or frequency utilization.
Network nodes equipped with a large number of antennas, as is the case for communication systems applying massive MIMO, can simultaneously schedule multiple user equipments at the same time and/or in the same frequency band and communicate with these user equipments using linear signal processing approaches (for example based on maximum-ratio (MR) and/or zero-forcing (ZF) algorithms). This enables handling of increasing data traffic amounts without necessarily requiring denser network deployment. Furthermore, each network node can control the interference that it causes to its local area in communication systems applying massive MIMO.
Using a large number of antennas at the network node and appropriately chosen precoding results in an effective channel between the network node and the user equipment (UE) that is stable or substantially stable over time and frequency. An effective channel having this property may be referred to as a hardened channel environment, and the approach to achieve it may be referred to as channel hardening.
Channel hardening can be utilized to simplify power control and adaptive modulation and coding. Since the channel variation is removed or at least (significantly) reduced by channel hardening, the adaptation can be determined over a much larger time/frequency scale, which is a benefit of massive MIMO over conventional radio access technologies.
In a massive MIMO system, the capacity increases with the number of antennas for all channels that utilize the channel state information (CSI) for precoding, or beam forming.
However, channels that do not utilize transmitter side CSI do not demonstrate this capacity advantage. Examples of channels that do not utilize CSI are some control channels such as scheduling request (SR) channels and random access channels (RACH) in UMTS LTE (Universal Mobile Telecommunication Standard, Long Term Evolution, advocated by the Third Generation Partnership Program—3GPP). Thus, when traffic increases the relative overhead of such channels increases also. Typically, the resources dedicated to such channels need to increase substantially proportionally with the number of user equipments to avoid a high collision risk (e.g. high in relation to an accepted error rate; if, for example, the acceptable error rate is 1% the collision rate must be much smaller and a collision risk may be considered to be high if it is above, for example, 0.1%), while this is not the case for resources dedicated to channels that utilize CSI.
Therefore, there is a need for approaches to reduce the relative overhead of channels that do not utilize transmitter side CSI in massive MIMO systems.
More generally, there is a need for approaches that enable or facilitate discrimination between different transmitting apparatuses (e.g. resolving of collisions).